K-Means and Its Blind Spots

K-means needs no labels at all. Drop k random centroids into feature space, then loop:

• Assign every point to its nearest centroid
• Move each centroid to the mean of the points it just claimed
• Repeat until nothing moves

That's the whole algorithm — and it segments customers, groups documents, and compresses images across a huge share of industry.